AI-Driven Educational Transformation in Indonesia: From Learning Personalization to Institutional Management

Haetami Haetami

doi:10.35445/alishlah.v17i2.7448

AI-Driven Educational Transformation in Indonesia: From Learning Personalization to Institutional Management

Haetami Haetami

Abstract

The integration of Artificial Intelligence (AI) in Indonesia’s education sector is transforming personalized learning and institutional management, offering improvements in student engagement, administrative efficiency, and data-driven decision-making. However, widespread adoption remains limited due to technological disparities, algorithmic bias, data privacy concerns, and low AI literacy among educators, especially in rural and under-resourced areas. This study aims to explore the role of AI in Indonesian education, identify key implementation challenges, and propose strategic approaches for ethical and inclusive integration. Using a qualitative descriptive analysis, the research synthesizes data from academic literature, policy documents, and case studies to evaluate the current landscape of AI-driven educational transformation. Findings reveal critical gaps in digital infrastructure, regulatory policy, and educator readiness, which restrict the scalability and effectiveness of AI applications. While adaptive learning technologies have enhanced individualized instruction, their deployment is uneven, exacerbated by regional inequalities. AI also supports educational administration, yet unresolved concerns about data transparency and privacy persist. This study concludes by proposing a multi-stakeholder approach for sustainable and equitable AI integration within Indonesia’s educational context. Recommendations include targeted infrastructure development, AI literacy initiatives for educators, robust data governance frameworks, and culturally responsive AI solutions. These insights contribute to ongoing efforts to bridge the digital divide and optimize AI's potential in education.

Keywords

Artificial Intelligence, Personalized Learning, Educational Management, AI Ethics, Digital Equity

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DOI: https://doi.org/10.35445/alishlah.v17i2.7448